Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution

Yang Xiao; Ning Zhang; Jin Li; Wenjing Lou; Y. Thomas Hou

doi:10.1007/978-3-030-59013-0_30

Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution

Yang Xiao, Ning Zhang, Jin Li, Wenjing Lou, Y. Thomas Hou

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

39 Scopus citations

Abstract

The abundance and rich varieties of data are enabling many transformative applications of big data analytics that have profound societal impacts. However, there are also increasing concerns regarding the improper use of individual data owner’s private data. In this paper, we propose PrivacyGuard, a system that leverages blockchain smart contract and trusted execution environment (TEE) to enable individual’s control over the access and usage of their private data. Smart contracts are used to specify data usage policy, i.e., who can use what data under which conditions and what analytics to perform, while the distributed blockchain ledger is used to keep an irreversible and non-repudiable data usage record. To address the efficiency problem of on-chain contract execution and to prevent exposing private data on the publicly viewable blockchain, PrivacyGuard incorporates a novel TEE-based off-chain contract execution engine along with a protocol to securely commit the execution result onto blockchain. We have built and deployed a prototype of PrivacyGuard with Ethereum and Intel SGX. Our experiment result demonstrates that PrivacyGuard fulfills the promised privacy goal and supports analytics on data from a considerable number of data owners.

Original language	English
Title of host publication	Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings
Editors	Liqun Chen, Steve Schneider, Ninghui Li, Kaitai Liang
Pages	610-629
Number of pages	20
DOIs	https://doi.org/10.1007/978-3-030-59013-0_30
State	Published - 2020
Event	25th European Symposium on Research in Computer Security, ESORICS 2020 - Guildford, United Kingdom Duration: Sep 14 2020 → Sep 18 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12309 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th European Symposium on Research in Computer Security, ESORICS 2020
Country/Territory	United Kingdom
City	Guildford
Period	9/14/20 → 9/18/20

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

Blockchain
Data access and usage control
Privacy
Smart contract
Trusted execution

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-59013-0_30

Cite this

Xiao, Y., Zhang, N., Li, J., Lou, W., & Hou, Y. T. (2020). Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution. In L. Chen, S. Schneider, N. Li, & K. Liang (Eds.), Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings (pp. 610-629). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12309 LNCS). https://doi.org/10.1007/978-3-030-59013-0_30

Xiao, Yang ; Zhang, Ning ; Li, Jin et al. / Privacyguard : Enforcing private data usage control with blockchain and attested off-chain contract execution. Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings. editor / Liqun Chen ; Steve Schneider ; Ninghui Li ; Kaitai Liang. 2020. pp. 610-629 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{f01cbcc1180d46d69e283ed4b2fbb118,

title = "Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution",

abstract = "The abundance and rich varieties of data are enabling many transformative applications of big data analytics that have profound societal impacts. However, there are also increasing concerns regarding the improper use of individual data owner{\textquoteright}s private data. In this paper, we propose PrivacyGuard, a system that leverages blockchain smart contract and trusted execution environment (TEE) to enable individual{\textquoteright}s control over the access and usage of their private data. Smart contracts are used to specify data usage policy, i.e., who can use what data under which conditions and what analytics to perform, while the distributed blockchain ledger is used to keep an irreversible and non-repudiable data usage record. To address the efficiency problem of on-chain contract execution and to prevent exposing private data on the publicly viewable blockchain, PrivacyGuard incorporates a novel TEE-based off-chain contract execution engine along with a protocol to securely commit the execution result onto blockchain. We have built and deployed a prototype of PrivacyGuard with Ethereum and Intel SGX. Our experiment result demonstrates that PrivacyGuard fulfills the promised privacy goal and supports analytics on data from a considerable number of data owners.",

keywords = "Blockchain, Data access and usage control, Privacy, Smart contract, Trusted execution",

author = "Yang Xiao and Ning Zhang and Jin Li and Wenjing Lou and Hou, {Y. Thomas}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 25th European Symposium on Research in Computer Security, ESORICS 2020 ; Conference date: 14-09-2020 Through 18-09-2020",

year = "2020",

doi = "10.1007/978-3-030-59013-0_30",

language = "English",

isbn = "9783030590123",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "610--629",

editor = "Liqun Chen and Steve Schneider and Ninghui Li and Kaitai Liang",

booktitle = "Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings",

}

Xiao, Y, Zhang, N, Li, J, Lou, W & Hou, YT 2020, Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution. in L Chen, S Schneider, N Li & K Liang (eds), Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12309 LNCS, pp. 610-629, 25th European Symposium on Research in Computer Security, ESORICS 2020, Guildford, United Kingdom, 9/14/20. https://doi.org/10.1007/978-3-030-59013-0_30

Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution. / Xiao, Yang; Zhang, Ning; Li, Jin et al.
Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings. ed. / Liqun Chen; Steve Schneider; Ninghui Li; Kaitai Liang. 2020. p. 610-629 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12309 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Privacyguard

T2 - 25th European Symposium on Research in Computer Security, ESORICS 2020

AU - Xiao, Yang

AU - Zhang, Ning

AU - Li, Jin

AU - Lou, Wenjing

AU - Hou, Y. Thomas

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

Y1 - 2020

N2 - The abundance and rich varieties of data are enabling many transformative applications of big data analytics that have profound societal impacts. However, there are also increasing concerns regarding the improper use of individual data owner’s private data. In this paper, we propose PrivacyGuard, a system that leverages blockchain smart contract and trusted execution environment (TEE) to enable individual’s control over the access and usage of their private data. Smart contracts are used to specify data usage policy, i.e., who can use what data under which conditions and what analytics to perform, while the distributed blockchain ledger is used to keep an irreversible and non-repudiable data usage record. To address the efficiency problem of on-chain contract execution and to prevent exposing private data on the publicly viewable blockchain, PrivacyGuard incorporates a novel TEE-based off-chain contract execution engine along with a protocol to securely commit the execution result onto blockchain. We have built and deployed a prototype of PrivacyGuard with Ethereum and Intel SGX. Our experiment result demonstrates that PrivacyGuard fulfills the promised privacy goal and supports analytics on data from a considerable number of data owners.

AB - The abundance and rich varieties of data are enabling many transformative applications of big data analytics that have profound societal impacts. However, there are also increasing concerns regarding the improper use of individual data owner’s private data. In this paper, we propose PrivacyGuard, a system that leverages blockchain smart contract and trusted execution environment (TEE) to enable individual’s control over the access and usage of their private data. Smart contracts are used to specify data usage policy, i.e., who can use what data under which conditions and what analytics to perform, while the distributed blockchain ledger is used to keep an irreversible and non-repudiable data usage record. To address the efficiency problem of on-chain contract execution and to prevent exposing private data on the publicly viewable blockchain, PrivacyGuard incorporates a novel TEE-based off-chain contract execution engine along with a protocol to securely commit the execution result onto blockchain. We have built and deployed a prototype of PrivacyGuard with Ethereum and Intel SGX. Our experiment result demonstrates that PrivacyGuard fulfills the promised privacy goal and supports analytics on data from a considerable number of data owners.

KW - Blockchain

KW - Data access and usage control

KW - Privacy

KW - Smart contract

KW - Trusted execution

UR - http://www.scopus.com/inward/record.url?scp=85091585553&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85091585553&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-59013-0_30

DO - 10.1007/978-3-030-59013-0_30

M3 - Conference contribution

AN - SCOPUS:85091585553

SN - 9783030590123

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 610

EP - 629

BT - Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings

A2 - Chen, Liqun

A2 - Schneider, Steve

A2 - Li, Ninghui

A2 - Liang, Kaitai

Y2 - 14 September 2020 through 18 September 2020

ER -

Xiao Y, Zhang N, Li J, Lou W, Hou YT. Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution. In Chen L, Schneider S, Li N, Liang K, editors, Computer Security – ESORICS 2020 - 25th European Symposium on Research in Computer Security, ESORICS 2020, Proceedings. 2020. p. 610-629. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-59013-0_30

Privacyguard: Enforcing private data usage control with blockchain and attested off-chain contract execution

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this